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We present here a method to integrate geologic, topographic, and land-cover data in a geographic information system to provide a fine-scale, spatially explicit prediction of sediment yield to support management applications. The method is fundamentally qualitative but can be quantified using preexisting sediment-yield data, where available, to verify predictions using other independent data sets. In the 674-km² Sespe Creek watershed of southern California, 30 unique “geomorphic landscape units” (GLUs, defined by relatively homogenous areas of geology, hillslope gradient, and land cover) provide a framework for discriminating relative rates of sediment yield across this landscape. Field observations define three broad groupings of GLUs that are well-associated with types, relative magnitudes, and rates of erosion processes. These relative rates were then quantified using sediment-removal data from nearby debris basins, which allow relatively low-precision but robust calculations of both local and whole-watershed sediment yields, based on the key assumption that minimal sediment storage throughout most of the watershed supports near-equivalency of long-term rates of hillslope sediment production and watershed sediment yield. The accuracy of these calculations can be independently assessed using geologically inferred uplift rates and integrated suspended sediment measurements from mainstem Sespe Creek, which indicate watershed-averaged erosion rates between about 0.6–1.0� mm� year⁻¹ and corresponding sediment yields of about 2� ×� 10³� t� km⁻²� year⁻¹. A spatially explicit representation of sediment production is particularly useful in a region where wildfires, rapid urban development, and the downstream delivery of upstream sediment loads are critical drivers of both geomorphic processes and land-use management.
